Feature Engineering

Feature engineering is one of the most strategic layers of classical machine learning. Feeding raw data directly into the model is often not enough; the data must be restructured, transformed, combined, and made more meaningful for the problem at hand. When done well, this process can dramatically improve learning performance. In tabular data, time series, and enterprise datasets, feature engineering often matters more than algorithm choice. Good feature engineering is another way of asking the model the right question.